For teams that detect defects before execution
Static Testing: Review that stops defects in design, not in production
We anticipate defects in code, design, and requirements, so that each release arrives with evidence and without surprises.
Trusted by organizations that stop defects in design, before they reach production
The problem isn’t code testing, it’s what’s missing behind it
When defects travel to production, the damage is already done
No static review at the source
Critical findings are discovered during acceptance testing or in production. SQL injection, credentials in code, financial logic errors — all reach the pipeline because no one looked for them earlier.
Review without criteria or scalability
There are peer reviews and static analysis, but without exit criteria or rules adjusted to risk. Two or three engineers are the bottleneck. The backlog grows faster than it closes.
AI without governance or traceability
Static analysis in the pipeline, AI generating recommendations that no one validates. Findings everywhere and no one prioritizing. When the audit asks what was accepted and why, there’s no defensible answer.
Whatever your scenario, the root cause is the same: defects are not sought where they are 100x cheaper to fix. That’s what we solve from the design phase.
The cost of a defect not detected in time
The same defect, 100 times more expensive if it reaches production
More expensive to fix a defect in production vs. detected in design
– IBM Systems Sciences Institute
| 67% |
of software defects |
| 45% |
of developers’ time |
| TMMi5 | First certification of its kind in the world MTP International |
Where does the real cost appear in your organization?
Critical findings (SQL injection, credentials in code, financial logic errors) detected in production, not in review
CNBV, Condusef, or PCI-DSS audits requesting evidence that the team reconstructs in days, not minutes
Emergency fixes that throw off the quarterly budget, release after release
Engineers spending 45% of their time on maintenance and bugs instead of building new capabilities (Gartner 2024)
Lagging behind organizations that already operate AI in review with governance and traceability
Uncontrolled backlog of findings — two or three engineers as a bottleneck for the entire review, while the backlog grows faster than it closes
MTP Framework, Omniatest® applied to Static Testing
Four reasons to trust MTP with your first static quality gate
Proven methodology, certified specialists, and controlled AI — all within a results-oriented model.
Omniatest® applied to static testing
Results over hours
Controlled AI (Human-in-the-Loop)
+200 ISTQB specialists. TMMi Level 5
What changes when testing is applied from the start
Before and after implementing static review with MTP
Objective criteria before release
Critical findings, severity, and minimum coverage defined. Management receives early visibility of risk, not surprises on launch day.
The 100x cost disappears from the budget
Defects detected in the static phase avoid the 100x cost of fixing them in production. Emergency fixes that previously disrupted the quarter no longer occur.
45% returns to new capabilities
Engineering time currently spent on maintenance and bugs returns to building new functionalities that generate business value.
Traceability integrated into the pipeline
Evidence readily available for CNBV, Condusef, PCI-DSS, or SOX audits. No reconstruction, no pre-audit stress, no findings due to lack of documentation.
Prioritization where risk is highest
Predictive AI focuses review efforts on modules with the highest financial, regulatory, and security criticality — not on the noise of thousands of minor findings.
Releases with evidence and no surprises
Each release arrives with acceptance criteria met, complete traceability, and the backing of TMMi Level 5 behind every control point.
CODE TESTING OPERATIONAL PROCESS
From zero to static quality gate in the real pipeline, in one sprint
Quick Assessment
Potential return, projected total cost, current coverage, and regulatory gaps. Delivered in 5 business days.
Identification of critical modules
Financial, regulatory, and security. We prioritize which code to review first based on impact and risk exposure.
Review Framework
Exit criteria, peer review, and static analysis by layer, aligned with applicable client regulations.
Pipeline integration
Jenkins, Azure DevOps, GitLab, or GitHub Actions, adjusted by module criticality. Quality gates active from the first sprint.
Controlled AI
Predictive prioritization, reduced false positives. Every critical decision goes through an MTP expert reviewer and is recorded with full traceability.
Continuous operation
Quarterly rule adjustment, progressive noise reduction, expansion of coverage to new modules as the backlog grows.
Proven scale in real projects
Proven scale in real projects, same evidence requirements
Financial Sector
Stabilized pipeline with integrated static quality gate without slowing down delivery pace
- +30 active initiatives with integrated static review
- +900K annual static analysis and review executions
- +20K hours of experience in regulated environments
- Multi-vendor, platform- and tool-agnostic model
“We stabilized our pipeline and today we release with greater confidence to Management.”
— IT Director, Financial Sector
Private Sector
Controlled release of critical systems without impact on internal clients or suppliers
- Quality gates active from the first implementation sprint
- Complete traceability available for CNBV, Condusef, PCI-DSS, and SOX audits
- Prioritization of findings by real impact, not by volume
- Certified ISTQB specialists with experience in core banking
We were able to release in a controlled manner without impact on internal clients and suppliers.
— IT Director, Private Sector
Verified operational scale
Proven scale in real projects
Issues Detected
Automated Test Cases
Testing Hours
Test Cases Designed
Code Testing FAQ
Everything you need to know before scheduling
What is the difference between peer review, formal inspection, and static analysis?
They are complementary. Peer review: another dev on the pull request. Formal inspection (Fagan style): structured process on critical requirements or code. Static analysis: tool on non-executed code, finds patterns at scale. All three are designed together in the MTP Framework to cover different risk layers without duplicating effort.
What static analysis tools does MTP use?
SonarQube, Checkmarx, Fortify, Veracode, Semgrep, GitHub Advanced Security, ESLint, SpotBugs, PMD, Bandit, and Roslyn. We support Java, .NET, Python, JavaScript, TypeScript, Go, C, and C++ with standardized SARIF output. Tool selection is defined during the Quick Assessment based on the client’s technology stack and regulatory profile.
Are the reports valid for regulatory audits?
Yes. Each finding has a complete record: model used, rule applied, expert reviewer, and justification for acceptance or rejection — in a sustainable format for CNBV, Condusef, PCI-DSS, and SOX. No need to reconstruct evidence when an audit arrives.
How long does it take for the first static quality gate to be operational?
The Quick Assessment is delivered in 5 business days with potential return, regulatory gaps, and projected cost. The first control points in the real pipeline — integrated into Jenkins, Azure DevOps, GitLab, or GitHub Actions — are active within the first implementation sprint.
Can the service operate on legacy code without tests or documentation?
Yes. We start by identifying modules of higher criticality and apply incremental rules, without requiring rewriting or prior documentation. Findings are prioritized by real impact, not by volume — so the team can act without being overwhelmed by an unmanageable list of issues.
What happens if static analysis generates too many false positives?
MTP’s Controlled AI layer prioritizes and filters findings before they reach the team: each alert goes through an MTP expert reviewer, who discards false positives and only escalates what has real technical evidence. The goal is to reduce noise, not generate more lists of issues.
Does static review replace dynamic or functional testing?
No. Static review and dynamic testing are complementary: the first detects defects without executing the code — earlier, cheaper —; the second validates behavior during execution. The MTP Framework designs them together to cover different risk layers without duplicating effort.
How is the static quality gate integrated without slowing down the pace of sprints?
Quality gates are activated by module criticality, not generally from day one: we start with the highest financial, regulatory, or security risk code, and integrate directly into the pipeline (Jenkins, Azure DevOps, GitLab, GitHub Actions) without blocking low-risk releases while the team adapts.
Which of the three scenarios is your organization in?
The 5-business-day Assessment maps your current level of defects reaching production, the cost of detecting them late, and the potential ROI of securing your code through static analysis, with a concrete deliverable to present to management.